Tag Archive for: Learning

We’re Slowly Learning About China’s Extensive Hacking Network

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The first two months of 2024 featured several revelations on the extent of China’s extensive hacking network. A joint cybersecurity advisory alert was recently posted from the CISA (Cybersecurity and Infrastructure Security Agency), the NSA, and the FBI on the extent to which Chinese state-backed hackers have had access to key U.S. infrastructures over the past five years, and planted malware that could trigger widespread disruptions to society. It was co-authored by the U.S. Department of Energy, the EPA, and the Transportation Security Administration, as well as by Canada’s, Australia’s, New Zealand’s and the United Kingdom’s cybersecurity centers.

Computer code on a screen with a skull representing a computer virus / malware attack.

I’ve reported in the past on China’s massive intellectual property theft and cyberespionage here and here. These activities included obtaining emails and communications from government officials.

The recent high-level alert escalates tensions

China’s state-backed hackers have embedded malware within critical U.S. infrastructure, such as programs used to manage clean drinking water, the power grid, and air traffic, among others. According to CISA director Jen Easterly at a hearing on the House Select Committee on the Chinese Communist Party,

This is truly an Everything Everywhere, All at Once scenario. And it’s one where the Chinese government believes that it will likely crush American will for the U.S. to defend Taiwan in the event of a major conflict there.

FBI Director Christopher Wray said that Chinese state-backed hackers have been lying dormant in critical U.S. infrastructure for five years, pre-positioning malware. In the event that there is a U.S.–China conflict, China can enact a cyberattack that will weaken U.S. operations. Intelligence analysts link this threat to a potential conflict over Taiwan, which the U.S. has promised to defend in the event China attacks the island. Taiwan operates as a de facto nation but is claimed by Beijing as part of the People’s Republic of China.

Wray has described China’s hacking program as larger than that of every nation combined:

In fact, if you took every single one of the F.B.I.’s cyberagents and intelligence analysts and focused…

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[Webinar] Artificial Intelligence & Machine Learning in the Age of Ransomware & Data Breaches – October 25th, 1:00 pm – 2:00 pm EDT | Association of Certified E-Discovery Specialists (ACEDS)

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Brian Wilson

Brian Wilson
Data Breach Advisory Services Managing Director
BDO

Brian leads our Data Breach Advisory services which assists organizations across the data breach lifecycle. We work with organizations to mitigate the risk of data breaches and identify when they occur; contain data breaches and minimize the impact on organizations; to holistically remediate vulnerabilities, harden defenses, incorporate lessons learned; and comply with regulatory reporting requirements, consumer data breach notifications laws, and third-party contractual obligations.

BDO’s ecosystem of capabilities, technologies, and partnerships are built on an uncompromising foundation of security, scalability, and defensibility. Our methodologies, agile approach, and tailored workflows assist organizations no matter where they are in the data breach lifecycle. Our subject matter expertise spans across legal, privacy, risk, compliance, crisis management, information governance, and cybersecurity. We adhere to industry standards, generally accepted frameworks and integrate leading, purpose-built, and emerging technologies including cloud, machine learning, and artificial intelligence to process information at scale and reduce the time it takes to report credible, reliable, and repeatable results with unwavering quality, consistency, and transparency.

Read Brian’s Full Bio

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IMEI | 🔍📱| #viral #shorts #technology #learning #knowledge

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IEEE Computer Society Emerging Technology Fund Recipient Introduces Machine Learning Cybersecurity Benchmarks

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Presentation at The Eleventh International Conference on Learning Representations (ICLR) debuts new findings for end-to-end neural network Trojan removal techniques

LOS ALAMITOS, Calif., May 5, 2023 /PRNewswire/ — Today, at the virtual Backdoor Attacks and Defenses in Machine Learning (BANDS) workshop during The Eleventh International Conference on Learning Representations (ICLR), participants in the IEEE Trojan Removal Competition presented their findings and success rates at effectively and efficiently mitigating the effects of neural trojans while maintaining high performance. Evaluated on clean accuracy, poisoned accuracy, and attack success rate, the competition’s winning team from the Harbin Institute of Technology in Shenzhen, with set HZZQ Defense, formulated a highly effective solution, resulting in a 98.14% poisoned accuracy rate and only a 0.12% attack success rate. This group will be awarded the first-place prize of $5,000 USD.

IEEE Computer Society Emerging Technology Fund Recipient Introduces Machine Learning Cybersecurity Benchmarks

“The IEEE Trojan Removal Competition is a fundamental solution to improve the trustworthy implementation of neural networks from implanted backdoors,” said Prof. Meikang Qiu, chair of IEEE Smart Computing Special Technical Committee (SCSTC) and full professor of Beacom College of Computer and Cyber Science at Dakota State University, Madison, S.D., U.S.A. He also was named the distinguished contributor of IEEE Computer Society in 2021. “This competition’s emphasis on Trojan Removal is vital because it encourages research and development efforts toward enhancing an underexplored but paramount issue.”

In 2022, IEEE CS established its Emerging Technology Fund, and for the first time, awarded $25,000 USD to IEEE SCSTC for the “Annual Competition on Emerging Issues of Data Security and Privacy (EDISP),” which yielded the IEEE Trojan Removal Competition (TRC ’22). The proposal offered a novel take on a cyber topic, because unlike most existing competitions that only focus on backdoor model detection, this competition encouraged participants to explore solutions that can enhance the security of neural networks. By developing general, effective, and efficient white box trojan removal techniques, participants have contributed to building trust in…

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