November 18, 2017, 7:10 am
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1 Philippine Peso = 0.07227 UAE Dirham
1 Philippine Peso = 2.22452 Albanian Lek
1 Philippine Peso = 0.03503 Neth Antilles Guilder
1 Philippine Peso = 0.34355 Argentine Peso
1 Philippine Peso = 0.02607 Australian Dollar
1 Philippine Peso = 0.03503 Aruba Florin
1 Philippine Peso = 0.03935 Barbados Dollar
1 Philippine Peso = 1.64187 Bangladesh Taka
1 Philippine Peso = 0.0327 Bulgarian Lev
1 Philippine Peso = 0.00742 Bahraini Dinar
1 Philippine Peso = 34.29713 Burundi Franc
1 Philippine Peso = 0.01968 Bermuda Dollar
1 Philippine Peso = 0.02667 Brunei Dollar
1 Philippine Peso = 0.13499 Bolivian Boliviano
1 Philippine Peso = 0.0645 Brazilian Real
1 Philippine Peso = 0.01968 Bahamian Dollar
1 Philippine Peso = 1.28247 Bhutan Ngultrum
1 Philippine Peso = 0.20681 Botswana Pula
1 Philippine Peso = 393.93939 Belarus Ruble
1 Philippine Peso = 0.03931 Belize Dollar
1 Philippine Peso = 0.02511 Canadian Dollar
1 Philippine Peso = 0.01951 Swiss Franc
1 Philippine Peso = 12.40988 Chilean Peso
1 Philippine Peso = 0.13051 Chinese Yuan
1 Philippine Peso = 59.13813 Colombian Peso
1 Philippine Peso = 11.08422 Costa Rica Colon
1 Philippine Peso = 0.01968 Cuban Peso
1 Philippine Peso = 1.83943 Cape Verde Escudo
1 Philippine Peso = 0.42677 Czech Koruna
1 Philippine Peso = 3.47954 Djibouti Franc
1 Philippine Peso = 0.12411 Danish Krone
1 Philippine Peso = 0.94451 Dominican Peso
1 Philippine Peso = 2.25075 Algerian Dinar
1 Philippine Peso = 0.2609 Estonian Kroon
1 Philippine Peso = 0.34652 Egyptian Pound
1 Philippine Peso = 0.53227 Ethiopian Birr
1 Philippine Peso = 0.01667 Euro
1 Philippine Peso = 0.04117 Fiji Dollar
1 Philippine Peso = 0.0149 Falkland Islands Pound
1 Philippine Peso = 0.01491 British Pound
1 Philippine Peso = 0.0895 Ghanaian Cedi
1 Philippine Peso = 0.92483 Gambian Dalasi
1 Philippine Peso = 177.2137 Guinea Franc
1 Philippine Peso = 0.14447 Guatemala Quetzal
1 Philippine Peso = 4.05313 Guyana Dollar
1 Philippine Peso = 0.15372 Hong Kong Dollar
1 Philippine Peso = 0.46232 Honduras Lempira
1 Philippine Peso = 0.12613 Croatian Kuna
1 Philippine Peso = 1.21291 Haiti Gourde
1 Philippine Peso = 5.19481 Hungarian Forint
1 Philippine Peso = 266.09603 Indonesian Rupiah
1 Philippine Peso = 0.06915 Israeli Shekel
1 Philippine Peso = 1.27847 Indian Rupee
1 Philippine Peso = 22.9634 Iraqi Dinar
1 Philippine Peso = 693.36875 Iran Rial
1 Philippine Peso = 2.02755 Iceland Krona
1 Philippine Peso = 2.47068 Jamaican Dollar
1 Philippine Peso = 0.01392 Jordanian Dinar
1 Philippine Peso = 2.21558 Japanese Yen
1 Philippine Peso = 2.03994 Kenyan Shilling
1 Philippine Peso = 1.37194 Kyrgyzstan Som
1 Philippine Peso = 79.10272 Cambodia Riel
1 Philippine Peso = 8.33333 Comoros Franc
1 Philippine Peso = 17.70956 North Korean Won
1 Philippine Peso = 21.5429 Korean Won
1 Philippine Peso = 0.00594 Kuwaiti Dinar
1 Philippine Peso = 0.01614 Cayman Islands Dollar
1 Philippine Peso = 6.52952 Kazakhstan Tenge
1 Philippine Peso = 163.2625 Lao Kip
1 Philippine Peso = 29.73239 Lebanese Pound
1 Philippine Peso = 3.02145 Sri Lanka Rupee
1 Philippine Peso = 2.44392 Liberian Dollar
1 Philippine Peso = 0.27873 Lesotho Loti
1 Philippine Peso = 0.05999 Lithuanian Lita
1 Philippine Peso = 0.01221 Latvian Lat
1 Philippine Peso = 0.02676 Libyan Dinar
1 Philippine Peso = 0.18535 Moroccan Dirham
1 Philippine Peso = 0.34406 Moldovan Leu
1 Philippine Peso = 1.02145 Macedonian Denar
1 Philippine Peso = 26.82015 Myanmar Kyat
1 Philippine Peso = 48.01181 Mongolian Tugrik
1 Philippine Peso = 0.15831 Macau Pataca
1 Philippine Peso = 6.91558 Mauritania Ougulya
1 Philippine Peso = 0.66706 Mauritius Rupee
1 Philippine Peso = 0.30638 Maldives Rufiyaa
1 Philippine Peso = 14.09681 Malawi Kwacha
1 Philippine Peso = 0.37473 Mexican Peso
1 Philippine Peso = 0.08186 Malaysian Ringgit
1 Philippine Peso = 0.27564 Namibian Dollar
1 Philippine Peso = 7.02479 Nigerian Naira
1 Philippine Peso = 0.60232 Nicaragua Cordoba
1 Philippine Peso = 0.16201 Norwegian Krone
1 Philippine Peso = 2.03758 Nepalese Rupee
1 Philippine Peso = 0.02897 New Zealand Dollar
1 Philippine Peso = 0.00757 Omani Rial
1 Philippine Peso = 0.01968 Panama Balboa
1 Philippine Peso = 0.06374 Peruvian Nuevo Sol
1 Philippine Peso = 0.06312 Papua New Guinea Kina
1 Philippine Peso = 1 Philippine Peso
1 Philippine Peso = 2.07261 Pakistani Rupee
1 Philippine Peso = 0.07062 Polish Zloty
1 Philippine Peso = 111.06651 Paraguayan Guarani
1 Philippine Peso = 0.07477 Qatar Rial
1 Philippine Peso = 0.07746 Romanian New Leu
1 Philippine Peso = 1.16854 Russian Rouble
1 Philippine Peso = 16.37721 Rwanda Franc
1 Philippine Peso = 0.07379 Saudi Arabian Riyal
1 Philippine Peso = 0.15368 Solomon Islands Dollar
1 Philippine Peso = 0.26269 Seychelles Rupee
1 Philippine Peso = 0.13104 Sudanese Pound
1 Philippine Peso = 0.16586 Swedish Krona
1 Philippine Peso = 0.02669 Singapore Dollar
1 Philippine Peso = 0.01491 St Helena Pound
1 Philippine Peso = 0.43695 Slovak Koruna
1 Philippine Peso = 149.94097 Sierra Leone Leone
1 Philippine Peso = 10.99961 Somali Shilling
1 Philippine Peso = 408.72688 Sao Tome Dobra
1 Philippine Peso = 0.17218 El Salvador Colon
1 Philippine Peso = 10.13341 Syrian Pound
1 Philippine Peso = 0.2756 Swaziland Lilageni
1 Philippine Peso = 0.64542 Thai Baht
1 Philippine Peso = 0.04872 Tunisian Dinar
1 Philippine Peso = 0.04538 Tongan paʻanga
1 Philippine Peso = 0.07647 Turkish Lira
1 Philippine Peso = 0.13045 Trinidad Tobago Dollar
1 Philippine Peso = 0.59144 Taiwan Dollar
1 Philippine Peso = 43.97875 Tanzanian Shilling
1 Philippine Peso = 0.52076 Ukraine Hryvnia
1 Philippine Peso = 71.36954 Ugandan Shilling
1 Philippine Peso = 0.01968 United States Dollar
1 Philippine Peso = 0.57989 Uruguayan New Peso
1 Philippine Peso = 158.20543 Uzbekistan Sum
1 Philippine Peso = 0.19628 Venezuelan Bolivar
1 Philippine Peso = 446.89099 Vietnam Dong
1 Philippine Peso = 2.12515 Vanuatu Vatu
1 Philippine Peso = 0.05043 Samoa Tala
1 Philippine Peso = 10.9329 CFA Franc (BEAC)
1 Philippine Peso = 0.05313 East Caribbean Dollar
1 Philippine Peso = 10.93861 CFA Franc (BCEAO)
1 Philippine Peso = 1.9754 Pacific Franc
1 Philippine Peso = 4.91834 Yemen Riyal
1 Philippine Peso = 0.27568 South African Rand
1 Philippine Peso = 102.11531 Zambian Kwacha
1 Philippine Peso = 7.12121 Zimbabwe dollar

CTO reflections: Beyond the appliance

Michael Xie,Founder, President and CTO, Fortinet

FOR anyone reading the news regularly, it’s not hard to grasp that cyber threats are getting more sophisticated and damaging by the day. From a security technology provider’s perspective, I can add that tackling them is a fast mounting challenge for the millions of businesses that come under attack daily.

Modern cybersecurity technologies – assuming you have already put in place the right professionals, policies and processes − are a must but organizations deploying them need to look beyond the boxes that sit on their racks.

What underpins the security appliances is invisible, but plays a pivotal role in ensuring that those boxes block the threats that imperil your business. Threat intelligence − or more specifically, the security appliances’ ability to know the ins-and-outs of the evolving threat landscape and respond to them appropriately – is the fuel that powers your cyber defenses.

Getting timely, accurate and predictive threat intelligence is much tougher than it sounds. It calls for a robust R&D set-up, which comprises a few components:

Divide and conquer − In many aspects of business, large teams equate to large outputs. When trying to outsmart well motivated cybercriminals, however, following conventional wisdom seldom works well. In my experience, an effective threat research organisation should be made up of many small teams, with each team dedicated to a particular type of threat. Creating such research focuses boosts each team’s specialization and competency − leading to faster discovery of threats, and the identification of more threats − while shortening customer response times to incidents.

Stay fleet-footed − Threat research teams must be nimble. The threat landscape is highly dynamic, changing by the day, or even hours and minutes. The teams must be able to adjust their priorities and refocus on the fly. At Fortinet, for instance, based on our projections of how the threat landscape will evolve, research plans are updated. From the new directions identified, researchers with the most appropriate skill sets are selected to join specific task forces to delve into those emerging threats.

Examples of such threats in recent times include IoT, ransomware and autonomous malware.

See the big picture − Researchers must be encouraged to think big and pursue their own interests, even if those interests don’t have a direct link to the company’s products. Research on IoT vulnerabilities, for instance, can deepen an enterprise security provider’s understanding of the threat landscape.

Hone your instincts − Research leaders must train their teams to develop the acumen to identify a threat as important before that fact becomes obvious to all. Good threat researchers, for instance, have been warning for years that IoT vulnerabilities are the next big menace − before the Mirai IoT botnet appeared last September and made it plain to the world. Threats emerge and evolve swiftly. If a security provider is slow to research on them and react, its customers will be slow to get protected.         
Amass data – The more data a threat research team has access to, the greater the potential of its research outcome. Enlightened research organizations share – not hoard – information. At Fortinet, for example, beyond tapping the 3 million sensors we have deployed around the globe, we actively exchange threat intelligence with organizations like INTERPOL, NATO, KISA and other security technology providers through the Cyber Threat Alliance. In recent months, we have also succeeded in bringing on board more government entities and carriers globally. That’s a positive development, as it helps all parties build a bigger threat database to monitor, block and trace malware back to their sources.

Invest in research technology – The days of manually analyzing threat information have long passed us by. Effective research teams need advanced tools to interpret and correlate the reams of data coming through to them every second. While today we have Content Pattern Recognition Languages (CPRLs) to help identify thousands of current and future virus variants with a single signature, the future belongs to technologies like big data analytics and artificial intelligence. Soon, AI in cybersecurity will constantly adapt to the growing attack surface. Today, human beings are performing the relatively complex tasks of connecting the dots, sharing data and applying that data to systems. In future, a mature AI system will be able to automate many of these complex decisions on its own.

No matter how advanced AI becomes, however, full automation – or the passing of 100% of the control to machines to make all the decisions all the time – is not attainable. Human intervention will still be needed. Big data and analytics platforms allow malware progression to be predicted but not malware mutation. Only the human mind could have foreseen that ransomware like Wannacry would embed the National Security Agency’s vulnerability exploits to propagate on unpatched systems.

Malware evolution will intrinsically follow human evolution and how people blend new technologies into their everyday life. If in the coming years, for instance, self-driving cars and wearable IoT find widespread adoption, cybercriminals will – as they have always done – find ways to ride the wave and exploit those cars and devices. Likewise, cryptocurrencies, if they continue to find favor at the rate they gained momentum this year, will attract herds of hackers.

The concept of automation is opening up many new possibilities for cybercriminals, and turning up the heat on organizations. As hackers step up the amount of automation in their malware, attacks will not only come at organizations faster, they will also reduce the time between breach and impact, and learn to avoid detection. Increasingly, firms will need to respond in near real time − in a coordinated fashion across the distributed network ecosystem, from IoT to the cloud. Not many enterprises have the capability to do this today, and that’s something CIOs should start worrying about.
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Column of the Day

Thumbs up and down at Asean

By JOSE BAYANI BAYLON | November 17,2017
‘This is the issue of the general public’s grasp of what it means for our country to be part of a greater, regional association of nations.’

Opinion of the Day

Onward: Planned Parenthood; Human Rights summit

By DAHLI ASPILLERA | November 17, 2017
‘Congratulations to the country’s PNP, AFP and all law enforcers, for a productive, uninterrupted, impressive Asean Summit. Great talents had put together a successful show.’