January 22, 2018, 12:51 am
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1 Philippine Peso = 0.07248 UAE Dirham
1 Philippine Peso = 2.15117 Albanian Lek
1 Philippine Peso = 0.03513 Neth Antilles Guilder
1 Philippine Peso = 0.37432 Argentine Peso
1 Philippine Peso = 0.02466 Australian Dollar
1 Philippine Peso = 0.03513 Aruba Florin
1 Philippine Peso = 0.03947 Barbados Dollar
1 Philippine Peso = 1.63391 Bangladesh Taka
1 Philippine Peso = 0.0315 Bulgarian Lev
1 Philippine Peso = 0.00743 Bahraini Dinar
1 Philippine Peso = 34.55654 Burundi Franc
1 Philippine Peso = 0.01974 Bermuda Dollar
1 Philippine Peso = 0.02619 Brunei Dollar
1 Philippine Peso = 0.13539 Bolivian Boliviano
1 Philippine Peso = 0.06307 Brazilian Real
1 Philippine Peso = 0.01974 Bahamian Dollar
1 Philippine Peso = 1.25863 Bhutan Ngultrum
1 Philippine Peso = 0.19114 Botswana Pula
1 Philippine Peso = 395.1056 Belarus Ruble
1 Philippine Peso = 0.03943 Belize Dollar
1 Philippine Peso = 0.02465 Canadian Dollar
1 Philippine Peso = 0.01899 Swiss Franc
1 Philippine Peso = 11.98717 Chilean Peso
1 Philippine Peso = 0.12629 Chinese Yuan
1 Philippine Peso = 56.09039 Colombian Peso
1 Philippine Peso = 11.14821 Costa Rica Colon
1 Philippine Peso = 0.01974 Cuban Peso
1 Philippine Peso = 1.78074 Cape Verde Escudo
1 Philippine Peso = 0.40983 Czech Koruna
1 Philippine Peso = 3.49517 Djibouti Franc
1 Philippine Peso = 0.12017 Danish Krone
1 Philippine Peso = 0.94356 Dominican Peso
1 Philippine Peso = 2.24754 Algerian Dinar
1 Philippine Peso = 0.25256 Estonian Kroon
1 Philippine Peso = 0.34873 Egyptian Pound
1 Philippine Peso = 0.537 Ethiopian Birr
1 Philippine Peso = 0.01614 Euro
1 Philippine Peso = 0.03952 Fiji Dollar
1 Philippine Peso = 0.01423 Falkland Islands Pound
1 Philippine Peso = 0.01424 British Pound
1 Philippine Peso = 0.08955 Ghanaian Cedi
1 Philippine Peso = 0.95481 Gambian Dalasi
1 Philippine Peso = 177.50149 Guinea Franc
1 Philippine Peso = 0.14478 Guatemala Quetzal
1 Philippine Peso = 4.06335 Guyana Dollar
1 Philippine Peso = 0.15424 Hong Kong Dollar
1 Philippine Peso = 0.4645 Honduras Lempira
1 Philippine Peso = 0.11993 Croatian Kuna
1 Philippine Peso = 1.2536 Haiti Gourde
1 Philippine Peso = 4.98796 Hungarian Forint
1 Philippine Peso = 262.6801 Indonesian Rupiah
1 Philippine Peso = 0.06734 Israeli Shekel
1 Philippine Peso = 1.2595 Indian Rupee
1 Philippine Peso = 23.36688 Iraqi Dinar
1 Philippine Peso = 722.49855 Iran Rial
1 Philippine Peso = 2.02684 Iceland Krona
1 Philippine Peso = 2.44306 Jamaican Dollar
1 Philippine Peso = 0.01395 Jordanian Dinar
1 Philippine Peso = 2.18305 Japanese Yen
1 Philippine Peso = 2.02388 Kenyan Shilling
1 Philippine Peso = 1.36803 Kyrgyzstan Som
1 Philippine Peso = 79.05665 Cambodia Riel
1 Philippine Peso = 8.11131 Comoros Franc
1 Philippine Peso = 17.76199 North Korean Won
1 Philippine Peso = 21.05013 Korean Won
1 Philippine Peso = 0.00592 Kuwaiti Dinar
1 Philippine Peso = 0.01618 Cayman Islands Dollar
1 Philippine Peso = 6.40616 Kazakhstan Tenge
1 Philippine Peso = 163.40439 Lao Kip
1 Philippine Peso = 29.70989 Lebanese Pound
1 Philippine Peso = 3.03631 Sri Lanka Rupee
1 Philippine Peso = 2.51372 Liberian Dollar
1 Philippine Peso = 0.24018 Lesotho Loti
1 Philippine Peso = 0.06017 Lithuanian Lita
1 Philippine Peso = 0.01225 Latvian Lat
1 Philippine Peso = 0.02645 Libyan Dinar
1 Philippine Peso = 0.1822 Moroccan Dirham
1 Philippine Peso = 0.33221 Moldovan Leu
1 Philippine Peso = 0.99072 Macedonian Denar
1 Philippine Peso = 26.54431 Myanmar Kyat
1 Philippine Peso = 47.6416 Mongolian Tugrik
1 Philippine Peso = 0.15887 Macau Pataca
1 Philippine Peso = 6.94691 Mauritania Ougulya
1 Philippine Peso = 0.64535 Mauritius Rupee
1 Philippine Peso = 0.3059 Maldives Rufiyaa
1 Philippine Peso = 14.08092 Malawi Kwacha
1 Philippine Peso = 0.36718 Mexican Peso
1 Philippine Peso = 0.07768 Malaysian Ringgit
1 Philippine Peso = 0.24178 Namibian Dollar
1 Philippine Peso = 7.06532 Nigerian Naira
1 Philippine Peso = 0.6045 Nicaragua Cordoba
1 Philippine Peso = 0.15516 Norwegian Krone
1 Philippine Peso = 2.01397 Nepalese Rupee
1 Philippine Peso = 0.02711 New Zealand Dollar
1 Philippine Peso = 0.00759 Omani Rial
1 Philippine Peso = 0.01974 Panama Balboa
1 Philippine Peso = 0.06337 Peruvian Nuevo Sol
1 Philippine Peso = 0.06241 Papua New Guinea Kina
1 Philippine Peso = 1 Philippine Peso
1 Philippine Peso = 2.17782 Pakistani Rupee
1 Philippine Peso = 0.06737 Polish Zloty
1 Philippine Peso = 110.75588 Paraguayan Guarani
1 Philippine Peso = 0.07183 Qatar Rial
1 Philippine Peso = 0.07523 Romanian New Leu
1 Philippine Peso = 1.11021 Russian Rouble
1 Philippine Peso = 16.49398 Rwanda Franc
1 Philippine Peso = 0.07401 Saudi Arabian Riyal
1 Philippine Peso = 0.15294 Solomon Islands Dollar
1 Philippine Peso = 0.26317 Seychelles Rupee
1 Philippine Peso = 0.13811 Sudanese Pound
1 Philippine Peso = 0.15903 Swedish Krona
1 Philippine Peso = 0.02605 Singapore Dollar
1 Philippine Peso = 0.01423 St Helena Pound
1 Philippine Peso = 0.43825 Slovak Koruna
1 Philippine Peso = 150.5822 Sierra Leone Leone
1 Philippine Peso = 11.09138 Somali Shilling
1 Philippine Peso = 395.67793 Sao Tome Dobra
1 Philippine Peso = 0.17269 El Salvador Colon
1 Philippine Peso = 10.16341 Syrian Pound
1 Philippine Peso = 0.24082 Swaziland Lilageni
1 Philippine Peso = 0.62838 Thai Baht
1 Philippine Peso = 0.04813 Tunisian Dinar
1 Philippine Peso = 0.04392 Tongan paʻanga
1 Philippine Peso = 0.07512 Turkish Lira
1 Philippine Peso = 0.1331 Trinidad Tobago Dollar
1 Philippine Peso = 0.57902 Taiwan Dollar
1 Philippine Peso = 44.22736 Tanzanian Shilling
1 Philippine Peso = 0.56937 Ukraine Hryvnia
1 Philippine Peso = 71.46241 Ugandan Shilling
1 Philippine Peso = 0.01974 United States Dollar
1 Philippine Peso = 0.56325 Uruguayan New Peso
1 Philippine Peso = 160.3513 Uzbekistan Sum
1 Philippine Peso = 0.19686 Venezuelan Bolivar
1 Philippine Peso = 447.97712 Vietnam Dong
1 Philippine Peso = 2.03691 Vanuatu Vatu
1 Philippine Peso = 0.0496 Samoa Tala
1 Philippine Peso = 10.5818 CFA Franc (BEAC)
1 Philippine Peso = 0.05329 East Caribbean Dollar
1 Philippine Peso = 10.49813 CFA Franc (BCEAO)
1 Philippine Peso = 1.92441 Pacific Franc
1 Philippine Peso = 4.9329 Yemen Riyal
1 Philippine Peso = 0.24034 South African Rand
1 Philippine Peso = 102.41761 Zambian Kwacha
1 Philippine Peso = 7.14229 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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